A new early detection system for bladder cancer based on urine analysis
Fundación para la Investigación Biomédica del Hospital Universitario 12 de Octubre, Madrid, Spain
Bladder cancer has a high incidence and a recurrence rate of over 70 %. For diagnosis and monitoring, patients undergo multiple invasive and costly procedures (two to four times a year for at least five years), making it the most expensive cancer disease per patient for health systems. For more than 30 years, a type of immunotherapy has been used to prevent recurrence and progression of the disease, benefiting about 50 % of patients; however, there is still no indicator to predict who will respond adequately to this treatment.
The team has developed a diagnostic tool for early detection of bladder cancer. It is a non-invasive diagnostic and monitoring system that has been shown to be more than 90 % accurate. The system is based on the detection of two RNA molecules in patients' urine. Furthermore, they have designed an electronic device for the automatic and direct detection of these molecules in urine which streamlines and simplifies the process, and which is now being evaluated. In addition, they have developed a non-invasive system that helps predict the response each patient will have to the standard treatment for bladder cancer that induces severe inflammation and pain. Predicting this response will avoid suffering for patients who cannot benefit from such treatment, and will save unnecessary costs for the healthcare system.
The project will work on validating the diagnostic tool, the electronic device and the prediction system. Its implementation would mean a significant improvement in the quality of life of bladder cancer patients, who would no longer have to undergo continuous invasive and painful treatments (currently, a patient is subjected to a total of 10 to 40 interventions during the follow-up years) and would significantly reduce the costs of these interventions for health systems.
BlaDimiR, non-invasive urine-based diagnostic and therapy response predictor for bladder cancer